scholarly journals A global system for mobile communications-based electrical power consumption for a non-contact smart billing system

Author(s):  
Ihsan Jabbar Hasan ◽  
Bushra Mahmoud Waheib ◽  
Nahla Abdul Jalil Salih ◽  
Nadhir Ibrahim Abdulkhaleq

<span>This paper proposes a cheap solution to be a starting point for building smart electrical power billing systems. Electrical power has many challenges issues in Iraq, one of these challenges and the most important is the Billing system. The smart power meter uses an Arduino Uno as the core for controlling the sensed data and transmits it to the electrical power unit for billing services. The system is constructed with two parts: the transmitting unit measures the current, voltage, power and power factor through the compact new sensor PZEM-004T. The data sensed and processed by the microcontroller which displayed the KWh on (2*16 LCD) display. This data also transmitted to the electrical power company unit via the global system for mobile communications (GSM) module (SIM900A) which is a dual band GSM/GPRS-</span><span>general packet radio service</span><span> modem. The receiving part is mainly dedicated for collecting the required consumed power data via the same (SIM900A) module and also can display it using (2*16 LCD) display. For the sake of saving these data, the receiver part uses SD ram for such purposes. With such proposed system the electrical power company can control and collect their fees monthly without loss and with minimum cost.</span>

2014 ◽  
Vol 118 (1203) ◽  
pp. 523-539 ◽  
Author(s):  
R. Zardashti ◽  
A. A. Nikkhah ◽  
M. J. Yazdanpanah

AbstractThis paper focuses on the trajectory planning for a UAV on a low altitude terrain following/threat avoidance (TF/TA) mission. Using a grid-based approximated discretisation scheme, the continuous constrained optimisation problem into a search problem is transformed over a finite network. A variant of the Minimum Cost Network Flow (MCNF) to this problem is then applied. Based on using the Digital Terrain Elevation Data (DTED) and discrete dynamic equations of motion, the four-dimensional (4D) trajectory (three spatial and one time dimensions) from a starting point to an end point is obtained by minimising a cost function subject to dynamic and mission constraints of the UAV. For each arc in the grid, a cost function is considered as the combination of the arc length, fuel consumption and flight time. The proposed algorithm which considers dynamic and altitude constraints of the UAV explicitly is then used to obtain the feasible trajectory. The resultant trajectory can increase the survivability of the UAV using the threat region avoidance and the terrain masking effect. After obtaining the feasible trajectory, an improved algorithm is proposed to smooth the trajectory. The numeric results are presented to verify the capability of the proposed approach to generate admissible trajectory in minimum possible time in comparison to the previous works.


1979 ◽  
Vol 6 (1) ◽  
pp. 120-128
Author(s):  
Craig J. Miller ◽  
Juarez Accioly

Precast, prestressed segmental box-girder bridges are now accepted as an economical alternative for spans over 150 ft (46 m). Decisions about cross-sectional dimensions made during preliminary design can have a substantial influence on the final cost of the bridge. To help the designer obtain an economical starting point for a final design, a program was written to determine section dimensions and midspan and pier prestressing steel areas to give minimum cost. Since a preliminary design is obtained, the analysis techniques and design criteria have been simplified to reduce computation. The design produced by the program will satisfy AASHTO specification requirements and the recommendations of the PCI Bridge Committee. The optimization algorithm used is the generalized reduced gradient technique. To demonstrate the program capabilities, three example problems are discussed. The results indicate that optimum span-depth ratios are approximately 24 for the cost ratios used. The cost of the optimum design does not seem to be too sensitive to the ratio of concrete cost to prestressing steel cost.


Author(s):  
Swati Dhandade

This paper presents a dual-band MIMO antenna design with compact size for 5G communication under 6 GHz band frequency. The metallic monopole stub structure is used to miniaturization of antenna. The L-shape monopole antenna is modified by adding semi-circular element in radiating structure of monopole to obtain dual-band resonance. The High isolation is achieved by employing T-shaped stub in ground plane.It has compact size is 45 mm × 25 mm × 1.6 mm3. The proposed Dual Band MIMO antenna has been design on FR4 material with ɛr = 4.4 with 1.6 thickness. The proposed antenna has 5G application in the bands of 2.5 GHz (2.34 GHz-2.62 GHz) and 3.5 GHz (3.20 GHz-5.20 GHz). The bandwidth of antenna getting 320MHz and 2500MHz at 2.5GHz and 3.5GHz respectively. The Isolation (S21) of proposed antenna is -31.2 dB at 2.5 GHz and -19.5 dB at 3.5 GHz. VSWR is less than 1.06 for both the bands. The designed dual band MIMO antenna covers 5G bands of 2.3-2.4GHz (n30/n40), 2.4-2.5GHz (n7/n38/n41/n90), and 3.2-5.2GHz (n77/n78/n80). The experimental and simulated results observed good matching except some slight variation. This proposed dual band MIMO antenna is suitable for 5G mobile Communications.


There are a host of difficult issues with scheduling, operation, and control of integrated power systems. The electricity sector is changing rapidly, and one of the most important concerns is deciding operational strategies to meet electricity demand. It is a greater challenge to satisfy customer demand for power at a minimum cost. The operating characteristics of all generators may be different. In general, operating cost is not proportionate to the performance of these generators. Therefore challenge for power utilities to balance the total load between generators. For a specific load condition on energy systems, Economic Dispatch(ED) seeks to reduce the fuel costs of power generation units. Moreover, energy utilities have also an important task to reduce gaseous emission. So the ED problem can be recognized as a complicated multi-objective optimization problem (MOOP) with two competing targets, the minimal cost of fuel and the minimum emissions effects. This paper presented an efficient method, hybrid of particle swarm optimization (PSO) and a learning-based optimization (TLBO) for combined environmental issues because of gaseous emission and economic dispatch (CEED) problems. The results were shown and verified by PSO and TLBO for standard 3 and 6-generator frameworks with combined issues of emission and economic dispatch taking into account line losses and prohibited zones (POZs) on hourly demand for 24 hours


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